Corinium

JUNE 6, 2019

It is also important to have a strong test and learn culture to encourage rapid experimentation. Newer methods can work with large amounts of data and are able to unearth latent interactions. One approach is to use NLP techniques to analyze actual call center interactions with customers.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Business Over Broadway

MAY 22, 2019

For those of you who are interested, here is Gartner’s latest (2018) hype cycle on emerging technologies. According to Gartner, companies need to adopt these practices: build culture of collaboration and experimentation; start with a 3-way partnership among executives leading digital initiative, line of business and IT.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

Domino Data Lab

FEBRUARY 4, 2019

Spoiler alert: a research field called curiosity-driven learning is emerging at the nexis of experimental cognitive psychology and industry use cases for machine learning, particularly in gaming AI. Ensure a culture that supports a steady process of learning and experimentation. This is not that. Or something.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Domino Data Lab

AUGUST 22, 2019

Instead, we recommend using the bokeh library to create a highly interactive—and actionable—plot, as with the code provided in Example 11.11. Interactive bokeh plot of two-dimensional word-vector data. Interactive bokeh plot of two-dimensional word-vector data. produces the interactive scatterplot in Figure 11.9

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Domino Data Lab

MAY 8, 2019

2018-06-21). If your “performance” metrics are focused on predictive power, then you’ll probably end up with more complex models, and consequently less interpretable ones. They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

O'Reilly on Data

MAY 11, 2020

Many of the models you interact with are mediated through screens, and there’s no shortage of news about how many of us spend our lives glued to them. It predates recommendation engines, social media, engagement metrics, and the recent explosion of AI, but not by much. Let’s start by looking at how models impact us.

Modeling 190

Modeling Advertising Recreation/Entertainment Metrics 190